The AI Learning Revolution: Moving from Participation to Proficiency

Speaker A: Bring out the talent. Bring out the talent.

Speaker B: Bring out the talent.

Speaker C: Welcome to Bring out the Talent, a podcast featuring learning and development experts discussing innovative approaches and industry insights. Tune in to hear our talent help develop yours. Now here are your hosts, TTA CEO and President Maria Melfa and Talent Manager Jocelyn Allen.

Speaker A: Hello. Hello, everybody. You know what, Dave, I think that we need to get an alternative little outro, ah, or intro rather, that says, and possibly John Lavager, um, just as a potential guest. Right. Because, um, although his Maria impressions are getting pretty solid, we want to allow him to have his own entity, you know, an identity here. So, uh, maybe we can work on that because. Because today I'm not joined by Maria. I'm joined by John Lavenger instead. Hi, Johnny boy.

Speaker D: Hi there, Jossie. How are you?

Speaker A: I'm doing great, my friend. Thank you for joining me. While Maria couldn' on what is, uh, slated to be a very excited episode about, um, some technology that's out there in the world that people may, may or may not have heard of, called, I hope I'm saying this correctly, AI. Um, so we're going to talk about that today with our guest, which, John, I know that you are very much, um, enveloped and you use AI on a regular basis and have taught me a lot, a lot about what it can do. So I'm excited to have you here so that you can, uh, make me a little bit more credible, so to speak.

Speaker D: Yes, for sure. Happy to be here. Awesome.

Speaker A: Uh, well, let's get started, shall we? Because I want to introduce our guest and get right into the topic at hand, which is the AI Learning Revolution. Moving from participation into proficiency. So in this episode we're diving into the AI Learning revolution and a model that moves us away from simple participants and toward, uh, guaranteed proficiency. We're exploring how a high accountability system powered by AI and human expertise can actually upgrade an organization's operating system in real time. So joining us today is one of our expert AI trainers and a true practitioner in the field, Ed Lance. Ed brings over 25 years of experience building talent systems for some of the most high stakes environments in the world, including NASA and the U.S. army. He's someone who stays hands on in the code every single day, and he's here to help us understand how AI is changing not just what we learn, but how we achieve true technical excellence. We're going to explore the 80% rule for mastery, how to integrate learning into the daily workflow without losing any productivity, and how L and D&HR leaders can finally use AI generated data to prove to the C suite that their teams are truly ready for the future. So welcome to the show, Ed. We're so happy to have you.

Speaker B: Thanks so much. I'm happy to be here. This is going to be exciting.

Speaker A: It sure is.

Speaker D: Yeah. This is great, Ed. I, I, wow. NASA, U.S. army.

Speaker A: Um, so you get more high stakes than that, right?

Speaker D: Right. Yeah. You, you've clearly had an incredible journey, um, from designing talent systems for NASA and the US army to now building out over a dozen advanced AI training programs. With that kind of background, including being a coder, why do you think simply knowing about a technology like AI is so different from actually being able to use it and change the way you teach it?

Speaker B: So I would say, you know, knowing about AI is like reading a recipe and that's good. Right? Using AI is like cooking the meal. So any student can kind of pass a quiz on predictive analytics or get a certificate. And that's not bad. But that doesn't help. Always help our company. Right. Uh, so in our model, a, uh, learner uses an AI coach and something like Python to build, uh, a custom dashboard pulling live CRM data. So they don't leave the course with just a piece of paper. They leave with a functional tool that predicts customer churn for their boss the very next day. And people tend to get pretty excited about that.

Speaker A: Love that. Because here in at TTA world, AI is like a part of our everyday occurrence. We love the technology, we love seeing how we can integrate it. Um, I call John, John GPT. Um, it's like a fun joke because he, like, there's always something that he's trying to see, like, what else can this do for us? How can it enable us to the future? Because we are the ones with the information, but how does it catapult it forward? Um, and I think a lot of that, as I kind of discussed in the beginning, um, giving John a little bit of a hard time, but truly he does teach me like different ways to use these things and see what it can do. Like, you know, just, just ask the questions and see what it brings out. So you and your experience, having taught and built many AI training tracks, was there a specific moment in your career where you realize kind of the same thing that AI could move from just being a subject that we study to actually bec the coach that helps the team, helps us learn, helps us advance our practices, whatever those may be.

Speaker B: Uh, I'll answer that this way. I'll tell you a little bit of a story first. I remember Honestly, I was getting to the point where I was like, oh, maybe, maybe I'll retire. The beach is sounding pretty nice right now. And, um, you know, I've done a lot with my career already. And, uh, as I begin to discover this stuff called AI a couple of years ago, um, I honestly, my first thought was, no way, I'm not going to let the kids have all the fun. This stuff is so cool. It's going to change the world. I want to be a part of that. And so I don't know if I had a precise moment, but it was a very gradual process of starting to see how AI impacted my own life, my own learning, helping me code faster and write faster. Um, stuff that used to take weeks, we got down to days and even hours. And so as a teacher, I just started sharing that stuff and the results have been, um, outstanding. Right. And now that said, there were definitely some aha moments. Right. Well, one of them was when I wrote my first retrieval augmented generation app, or rag, for those of you familiar with that. And another is when I saw this open Rails platform that we're going to talk about a little bit, uh, and just saw how it could accelerate the AI curve for almost any organization. And that was pretty exciting.

Speaker D: That's awesome. Yeah. I'm definitely always looking for new applications for AI and it just seems limitless. Um, and I love it, and it's what keeps me motivated with it. Um, you know, I know, I know. You're using a personalized AI assistant to give people real time support. So for the L&D HR leaders listening, how does that AI coach fundamentally change that stuck moment for a leader who's trying to master something new?

Speaker B: Yeah. So learners, learners get stuck, let's be honest. Right? And, um, you know, I've said for years in my programming classes, you don't have to be the smartest kid in class, you have to be the most stubborn. And that's really the way to learn programming. So my joke, um, around this one is with an AI coach, um, I don't have to feel stupid for too long, Right? And, uh, you will. If you're learning a hard, hard, challenging topic like coding, you're going to get frustrated, right? You're going to get those moments where you're like, wow, I'm just, I'm not getting it. It's taking too long. Um, and I think failing in front of a human can hurt my ego more or waste more time. Maybe I'm not quite as, as comfortable asking, but with this, with this tool that we've developed, you just kind of have safe accountability. So what you have to DO is score 80% on every lab to move forward. Right. That changes your mindset because you know now that every single lab is going to be checked. Hey, look, if you came to my class, I don't care how many days you had me or how much money you paid me, probably would not have time to grade every student's lab. This tool will grade every single lab, and then it scores that lab. And we use 80% as our baseline because we really like it. But you can move that up or down depending on your topic. But if you fail, then you have the option to say, you know what? I'm stubborn. I want to try this again. I will get it. Or you can push a button and say, you know what? I think I need some help. I'm going to schedule a little, um, time with the instructor via office hours.

Speaker A: I want to talk a little bit about that 80% competency, because, I mean, what's. I guess, why is this kind of rigor, I guess, better for a person's confidence or understanding? Uh, as you put it? Because, like, I, like, there's a couple things that I really liked about what you said, because I think the reasons why maybe some people are afraid of AI are some of what you mentioned could be a reason why they start using it. Right? Which is like, there's this little bit of a barrier, um, in the, In a human centric way that kind of, like, maybe protects some feelings as you're learning some things, which I think is a very real thing thing for people, um, just, you know, being emotional beings with, like, logical capabilities. Right. I learned that on the last podcast episode that we had. Um, but why. So what other reason does this 80%, like, really work for the rigor of the system? Because I feel like in other tools, um, or like, competency models, we're dealing with, like, maybe multiple choice or fill in the blank. Right. So how, how is this different? Um, value wise.

Speaker B: Yeah. So I think, first of all, the AI coach that we have will literally coach me as I'm going to try to help me get to that 80% level. And then the other thing I think about is really competency over just completion. Right. So, look, I'm a good test taker. I've taken a lot of tests throughout the years, and I, uh, can cram before a test and I can get the bubbles correct, but can I do the job when I get back to the job? And I think having that 80% completion in code Exercises really builds confidence, and it really proves that, hey, you know what, Whether I can pass a quiz or not, we can keep those in or dump them, but I can go back and actually code this stuff and make it work. So traditional training just lacks the time to review every student's work. So this is a place where AI really steps up and helps us accelerate.

Speaker D: That's great. So I know you're a big advocate for the human AI hybrid model with the live office hours. I mean, you were just alluding to that. Maybe you want to get some feedback from AI. Maybe you need to spend some time with the instructor. Why is that human connection still. Still an important component and still gives people the confidence to tackle complex subjects, you know, particularly topics like Python or Java.

Speaker B: Yeah, I think the short answer is because AI is an imperfect tool. And I like to say it's a power tool, um, which is very powerful. But be careful, right? Power tools can hurt you or, um, you know, you can use it improperly. And I think, at least for now, we need to see it as a collaborator. Somebody that, uh, literally when I code, even today, I treat AI as a, A coding partner, right. Um, it's my pair programming partner. And sometimes it has insights I don't have, and sometimes I pick up on things that AI didn't. So whether you're trying to understand a book, a video, or the AI coach is trying to explain something to you, it only goes so far. With a human there and having that safety net, you can go, oh, you've been there and done that. And how, how do I do this again? And I can say, let me show you what was meant here. This is what we meant. Right. Um, I think it's also important to note that when we say hybrid, uh, what we mean is having some of the learning be instructor led. Right? So, uh, immersive type project work, the most successful training I've ever seen. And if there was no limit on anybody's time or budget, that I would say you want to do is immersive type project work. Right. Delivered in a very Socratic approach. Give the student a problem, let them wrestle with that problem for a little bit, then come back and say, by the way, we solved the problem this way and here's why. We use this design or these patterns or this approach to solve the problem. And we're going to give you a little more time now to go back and refactor your code. And you just see the learning, um, really, really accelerate and people come out of the class and it really sticks with them. So I think the last thing I'll add there is with this approach AI, as you guys know, if, you know, machine learning, the AI will get smarter, but the training team gets smarter about the content too by having that, that trainer, uh, very engaged with that group of students, because every group of students can be a little bit different.

Speaker A: So regarding that then, because I'm going back to this kind of like, really what you said, hybrid, where I think the way to get people a little bit more and like, antiquated with it is to have this human idea of it. But again, like, it's not, but it, it's. I just feel like a lot of this track is allowing it to kind of behave that way where it meets you, where you're at, and then helps you enhance where you want to go. So this personalized learning that we're kind of like alluding to here, that, like in previous years, let's say even most recently, that like, personalized learning track was like choice A, choice B, right? Like, there's somebody created it for this purpose, and all they created was two tracks. So how is AI tailoring this, like, idea of personalized learning for organizations? And what, what does the human aspect of it, like, when we provide input, when we provide feedback, how does it adapt it to be like, more of that? This is your personal tutor with your personal journey versus, like, pick track A or track B. Like, how has it gotten us to evolve to that point?

Speaker B: Yeah, that's. That's a really good question. And I think here's the thing, right? So every instructor led in person class I've ever done. One of the hardest parts is, oh, I've got 12 or 16 people about to walk into this room, and all of them are in different places. Who do I teach to? Heck, if you're teaching public school, do you teach to the smartest kid or the kid that needs the most help? Right? You just, you don't know how to teach precisely to every single student. So imagine that you walk into this classroom and I'm your teacher, and you have a remote, and on stuff you want to know more about, you can raise your hand and say, hey, could you tell me more about that? And on stuff that you're like, I already know that I want to put my head down and try this, right? You could just push freeze on it, and the instructor would freeze and let you do your thing. So that's kind of the way this AI coach works. If you are an individual student, you're going through the same materials as everybody Else. But if you look at that topic and go, I know this. You are allowed to, um, skip or test out of it, either. Your choice. We let the organization kind of choose what they want to do there. Um, we do have one typically, uh, session every week where we bring everybody together to keep that kind of team approach. But individually, you get to skip over the parts that you're just bored with or already knew when you walked into class. And you get to ask for help either by repeating or by asking for a coach on the stuff that you're struggling with. So I think that all of us process the information different. This gives me a chance to work for a half hour, walk away, put my head down, and focus for two hours. Um, I often joke if you're, you know, you might want to go talk to a colleague. If you're a verbal processor like I am, you might want to walk around and talk to yourself a little bit. Right? And then you're like, oh, okay, now I get it. So I think, um, that's just fantastic there. Right? And the other thing this tool adds, and this approach adds to instructors is who do I spend time with? Right. If we're in a class and John's raising his hand all the time and Jocelyn isn't, gosh, uh, I guess John needed more help, but maybe not. Maybe Jocelyn just didn't feel comfortable, um, asking for help. Right.

Speaker D: It would likely be in reverse. Ed, just so you're aware, I literally

Speaker A: was just going to chime in and be like, yeah, very likely scenario that I would have trouble.

Speaker B: Yeah, I was trying to be nice anyway, so. But the point is, it'll pull me as an instructor. I can see their work. I can see who's spending how much time. I can see who's asking, you know, uh, for helper who hasn't got the labs done or who's getting 79% right or wherever they're at. And that pulls me to the right person at the right time. And, um, so ultimately, what we're saying to the students is, look, you must master these skills to an 80% competency level. There's a ton of support for you. And choose what kind of help helps you the most and choose your path, uh, that helps you the most.

Speaker D: So want to kind of shift gears just a little bit, Ed, I. I remember we had a client call, and one of the things you were mentioning was microdosing knowledge in just an hour to a day. And I'm wondering, how does. How does AI help someone stay in their daily workflow? So they can learn something in the morning and maybe even actually apply it later that day in the afternoon.

Speaker B: Yeah, so many lessons from my life here. Um, but I'll give you, I'll give you a silly one. Um, so on and off throughout my life, I've decided late in life I wanted to learn to play guitar, right? And uh, and by the way, I've, I've worked it out as a good teacher. If I live to be 230, I'm going to be an amaz, amazing rock star.

Speaker C: Okay?

Speaker B: So just be ready. But, uh, but what I've learned from teacher after teacher as I've tried to learn to play this instrument is 15 minutes a day is better than 6 hours on a Saturday, right? They all say it's just been proven over and over and over. And I've learned that. The same thing with my technology learning, right? For me it's early in the morning, I find that time and I spend, you know, 30 minutes to an hour focus on that thing. Sometimes longer, sometimes, uh, a little less. But that consistency really, really pays off and that, so that microdosing has a lot of other advantages that we retain it better. We don't have to travel and interrupt our daily or personal work to a quote the 10 training. And uh, and maybe most importantly I always joke is we don't have to fall behind on the hundreds of emails and dig ourselves out later, which I always hate when I come back from training. So um, so we're learning as we go. Which if you think about it is the way you learn most of what

Speaker A: you know in life, build the plane while flying it as they say, right? Which uh, is a very dramatic representation but, you know, also quite accurate, which is maybe not as dangerous. Um, but I, what I love about what you're doing is um, kind of like what you, what you said, learning as you go. And the idea that a lot of your students are bringing like an actual project to the scene and working through that as part of the training and the learning and the knowledge transfer that they're experiencing? So you use AI, you use Agile methodology to help these teams finish an actual project while they're going through it. So like, what, what has the effect been on the people who uh, on the students in your courses or the people on this journey of not only walking away with a certificate, but also something that they completed within that certificate at that time? Like, is that making a big impact?

Speaker B: It's making a huge impact. And I think, um, I always tread lightly on the agile question because to be Fair. We've done it wrong a lot of times. Okay. But I do think when Agile is done properly and you use AI tools properly, one of the things that happens I've seen with students over and over in teams is that they begin to realize again that developing software is fun. Right. Most of us got into this career because of the joy that solving problems provide us. We like that puzzle, we like wrestling with that, and we love the satisfaction of, um, achieving it. So I recognized very early when I was doing training that I was rarely the smartest person in the room. I always thought before I was a trainer, wow, that person must be the smartest person in the room. But I might be the most knowledgeable about my content, but the people we teach in IT are typically somewhere between pretty darn smart and completely brilliant. So this demands, in my opinion, an honest and a pragmatic approach. They need to see that we're about delivering better software faster and by doing it and helping others do it. So, specifically, when it comes to AI, most tech people, maybe all people, fall into two camps. They believe in AI or they don't. So I think they're like me when we answered the first kind of question you had. I have to show them how to be a proactive skeptic. Right? So, in other words, it's fine to be skeptical. Will this work for me? Um, but be proactive and start trying to apply it to your job every day. And the one thing I hear over and over and over is as people start to do it is, gosh, it's not as hard as I thought it was going to be. It sounded so intimidating. I remember personally when I was like, oh, my gosh, we've got to learn something new again. I'm going to go out and I'm going to code to, uh, it was an OpenAI call from Python. And when I got done, I just remember thinking, it can't, it can't be this easy. Like, that was it. Uh, so it was pretty straightforward. And I think people, the more they use AI, the more they kind of get that attitude. Um, so. And I think also because we've been there and done that and we've screwed up projects and we've made mistakes, uh, in our lives as instructors. I think the one thing that we get is what I call not street cred, but prison cred. And the idea is you've been trapped on failing projects too, and that's very frustrating for people. So, uh, I think all of those, um, really matter. Right? So it's not just About a certificate. It's about delivering finished work and getting better at my craft Ed.

Speaker D: Ah, we have. Speaking of things that we hear over and over, I hear all the time from clients, uh, L and D groups, HR groups about this desire to measure learning. And some organizations do, and some things are easier to measure than others. Um, but I'm wondering is, is there a role for AI in helping determine if we've moved the needle at an organization, um, and making sure people are really ready for their job or they are being more productive?

Speaker B: Yeah. I'll give you two answers, right. The first one's a little bit of a soft metric, but I just think it's so important when it specifically comes to learning. And that is ask participants after the class. And I'll say it this way, if we do a great job in a class and, and you guys know this, right? We don't have to advertise that class almost ever again because people will go and tell their friends, I learned so much at this class. It helped me so much. It just spreads like wildfire in an organization, right? So if they recommend their training to their friends, that's a good, good M metric, uh, to say, hey, we did our job as trainers right? Now, specifically around data, because I'm a data driven guy, I really like it. Um, so there's a couple of data points that I look for. And the first is, have we improved flow? Right. So are we delivering in the IT world more features of the same or better quality than we were before? Is the team processing stuff down our software assembly line? Right. And even if we're not doing it, this applies everywhere. Right. So did we reduce processing time on whatever activities added value to our customers? Right. Whether that's processing documents faster or getting stuff organized faster? Um, all of that is just improving flow. If we're not improving the flow and not getting more output, then why are we bothering? Right? So it better, better make it better than it was before. Uh, and then the other thing I think that I is popular in the industry that I really am a fan of is outcomes. Right. So I improved my website or whatever and I spend more time on a, on a product making it better. Well, did the customers use your product more? Right. Um, and, and can you tell from your net promoter scores or the subscriptions to your website, like the, the money that the company spent, uh, you know, invested their, their time and effort and talent into, did it get a return on investment from the customers that were using your product more, more excited about your product? Uh, those are the Things I look forward specific data.

Speaker A: It's one of the challenging things that I think I've witnessed, like witnessed is that um, we AI is a big efficiency tool. I think that's one of the biggest things that people can get behind is like how much easier and more promptly you can do like those time consuming tasks. And then of course beyond that and what your, your competency program um, really kind of does for teaching and allowing people to understand the knowledge level that they're at. But at the same time things are moving so fast with AI that it's like we're having this battle between like get moving on it. Cause that's when you become efficient. But oh my God, keep up with it because there it goes, right? Like there it goes, keep up. What else is it doing now? So what's like knowing how much it can do and how fast it's moving? Where's the risk here? Like what's the, where does the biggest risk lie for companies that are not getting on it as quickly as, as they should be, not moving with the pace or really just kind of behind and sticking with traditional methods versus integrating AI?

Speaker B: Yeah, I'll make a blanket statement about AI in general here. Right. And I'll use this little analogy. Um, years ago I watched the Internet come and we knew it was going to be a big thing. But the thing is if Jocelyn had a website and I didn't have a website, we were similar companies. I could go out and build a website and catch up. I um, don't think you can afford to fall behind in, in this arena. Right. If Your competitor uses AI to get 10 times or 100 times faster to you, if they capture market share while you're trying to catch up, they can slash prices, they can take more of your market share before you ever realize what happens. And how are you going to possibly afford to fall uh, behind that curve and still catch up again. So that's, that's my opinion. Um, I know others have different opinions but I really believe in that. I think that we're going to have to stay current, um, specifically regarding training. I think that current training models are well intentioned but there's a long list of studies with backing data that'll show you uh, a purely self paced training has not great completion rates, not great retention and it's just not as effective as we all hoped it would be. Nobody was, you know, is against it. It's just not, you know, the, the learning doesn't stick as much, the completion rates aren't as high as we'd all like for them to be. And so I think this kind of model says, you know what, uh, we're going to put it there, we're going to focus on competence over just completion. And you're going to um, cut that risk of falling behind the learning curve.

Speaker D: Yeah, it's a good point. We're moving at a pace that we haven't before. Um, you know, and this is beyond throwing more bodies at something. This is at a whole different scale. So point taken. Um, I've heard you in the past, Ed, describe your work as more than just upgrading an organization's operating system, but really is a cultural shift. And I'm hoping you can expand on that a bit. You know, what kind of cultural shift happens when a team realizes that they can actually master these complex AI tools in real time?

Speaker B: Uh, there's a lot of parallels here in what happens with strong agile teams too, right? I think in a word it's ownership. And uh, my degree's in management by the way, and my early training was in management. And uh, I, I, I say it took me 20 something years to learn that you don't manage people, you unleash them, right? You get out of the way. It turns out that most people want to do a good job if we'll just get out of the way. In fact, if we have time, let's talk about uh, what motivates people uh, later on. But so I think it's ownership, right? And fear is greatly reduced and replaced with, oh, I thought it was going to be a lot harder like I said earlier, right? And um, so as the fear and annoyance of having to change yet again gets reduced, there's this quiet confidence that starts to build in people and they realize they can control their own destiny. And then they start to go, wait a minute, you told me about this in class. But I can really use this tool to do this other thing that you didn't even understand about my job. And that's where the ownership and the excitement, um, comes from. And I think, you know, the, the example I use is the industrial revolution wasn't a problem for those willing to learn and willing to adapt. Others got, got left behind, right? And so I think there's a, uh, big shift when individuals and teams begin to solve their own problems and automate their, their boring work and help solve an organization wide problem. And it really is taking the principles and the practices that we teach in these classes and then going, you know what, I'm going to take them to my problem, set that stuff that we didn't even have time to talk about in class. And I'm going to really use them. And that's, that's when we win. That's the best, the best reward I get is when a student writes back, hey, I solved this problem with the tool. And it may be something that I was like, wow, we didn't even mention that in the curriculum.

Speaker D: It's, it's really interesting. Um, even amongst my team, um, on the sales team, they've really gotten, and we've, we've had, we have folks on the team that have varying levels of, of, um, experience with the various AI tools. And even over the last, I'd say six months watching, um, them go from, you know, just carefully using it, thinking of like one use case for it, maybe to just help create some, some language, um, for a proposal or something along those lines to now finding a ton of applications for it and having it be essentially a partner in their practice is, I mean, it's been a huge evolution. Um, so it's, that's great.

Speaker A: So let's talk about, in closing ed, um, about the skeptics, all right? Like the skeptical, skeptical side of things. Because as far as AI is concerned, I believe we're still in the very early adoption phase, right? Like, there is still 70, 75% of whomever in this, in this pool of people that have not used or adopted AI. So let's say you're sitting down with a chro. Who is that person, all right? Says, no way. I'm in the 75% for life. Um, what advice would you give them about adopting AI into their learning initiatives? How to get guaranteed proficiency and what it could actually change for the better in their roles or for their organization, rather.

Speaker B: Yeah. So a couple of things here, right? So I think first and foremost, it's not one and done. You are so right. It is absolutely changing faster than any of us can keep up. Right. There's no such thing as an AI expert. Um, it's changed since I went to sleep last night. Right? Um, so that, that knowledge and capabilities is going to continuously and rapidly evolve. And in fact, the bottleneck, the interesting twist here is the bottleneck isn't going to be technology anymore. It's able to teach itself and grow so fast that the bottleneck is probably going to be humans. Uh, Sam Altman, you know, the CEO of, uh, OpenAI, made a really candid admission that was radical to me, uh, just a few weeks ago. Right. He said, I still kind of run my workflow in very much the same way. Although I know that I could be using AI much more than I am. And I remember reading that going, wait, what? Sam Alan said this, right? Uh, it made me feel better because I'm like, if he's struggling, that makes me feel better because we're all struggling. Right? Uh, and so I think that's something to really keep in mind. And participation only training actually costs the company money because it just gives employees the confidence to use AI tools incorrectly. Right. Which means I can go write a lot of messy code, um, I can create bad data, um, and create a ton of technical debt. So what we don't want is people with false confidence. And um, so I will say this. Remember that I said humans will be the bottleneck. And for those of you who are students of uh, Eli Goldratt and the theory of constraints, the biggest thesis, the biggest thesis statement of his book is any improvements made anywhere except the bottleneck are an illusion. So in other words, if you have a factory and you uh, you are fixing how we put the windshields in faster, but it takes longer to put the motor of the car in. You're just going to have a bunch of cars and windshields, but they're incomplete cars, right? And you can't sell them. So we have to attack that one bottleneck. So if humans are the bottleneck, which I think they are rapidly becoming, right. Then the training model we're recommending needs to give every single employee a one on one tutor, something that was physically impossible and way too expensive before AI and let them gain that knowledge as rapidly as they can. That's my opinion on that.

Speaker D: So one, one last question for you, Ed. And you know, humans becoming the bottleneck kind of got me thinking in this direction. And for those that are tech savvy out there, what's your prediction on when we'll reach artificial general intelligence?

Speaker B: Um, two weeks after I'm dead. So I, uh, I, I, I don't think we're going to see it anytime soon. I think it's quite a bit in the future. I think there are a lot of hoops to jump through. But listen, I know, you know a fragment of, of what I need to know about AI and so do I think, um, a lot of people. So the people that get on YouTube and stuff and make insane predictions. Um, I don't know, it could happen faster than we thought. Some of AI has progressed a lot faster than I thought it would. But I don't think we're, we're going to be there in less than 10 years. That would be, I think, optimistic, to be honest. In my opinion, awesome.

Speaker A: We love a realistic point of view, so we appreciate that for sure. Um, let's go to something that doesn't require too much overthinking, um, and, you know, moves quickly, but not at AI's pace. Um, it's the TTA 10. Ed, we got some more questions for you. All right, let's hear it, David.

Speaker C: It's the TTA 10. 10 final questions for our guest.

Speaker A: Okay, Edward, we are on to the TTA 10 rapid fire questions. There's only 10 of them. There's gonna be, uh, 60 seconds on the clock, and the goal is to answer them as quickly as possible. When you achieve that, we will then go into celebration mode, in which case David will have something prepared to celebrate the Ed Lance. Okay? So no pressure. All in good fun. Are you ready?

Speaker B: I'm ready. Let's go.

Speaker A: Okay. All right. Daveed 60 seconds on the clock.

Speaker C: Place 60 seconds on the TTA 10 clock, beginning now.

Speaker A: Ed, what's a skill you have that has nothing to do with your career?

Speaker B: Uh, persistence and stubbornness.

Speaker A: What's a small daily habit that you do that makes a big difference in your routine?

Speaker B: Uh, I get up every morning and I read something.

Speaker A: Coffee or tea?

Speaker B: Coffee.

Speaker A: What's one word your team would use to describe you?

Speaker B: Intense.

Speaker A: If you could instantly master one new skill today, what would it be?

Speaker B: I'd love to advance my emotional intelligence. I think we can all get better there.

Speaker A: Hold that. What's the best piece of advice you ever received?

Speaker B: Never give up.

Speaker A: Are you early bird or a night owl?

Speaker B: Early bird.

Speaker A: If you could have a dinner date with anyone, living or dead, who would it be?

Speaker B: Wow.

Speaker C: Okay,

Speaker B: Eli Goldrap.

Speaker A: Um, what's a book that you recommend to everyone because you just love it so much?

Speaker B: The same one I just recommended, the Goal. And by the way, every time I read it, my income goes up, so I don't know how to give it a higher recommendation than that.

Speaker A: If you weren't in your current profession, what do you think you'd be doing?

Speaker B: Finance.

Speaker A: Okay, well, that's 10 questions. So, David, can we please have the results for ed?

Speaker C: Yes, remarkably, it came right down to the wire. But with the time of 59.2 seconds, Ed has achieved victory.

Speaker A: All with. Without AI. Ed. Look at that. Maybe there was. Maybe there was. Who knows? Maybe that's how we did it.

Speaker C: Although, let me ask you, Ed, you said your. Your dream dinner date would be Eli somebody. I didn't catch that Eli Gold rat.

Speaker B: He's the author of the Goal. And it's the book that probably has changed my life the most. Um, I'm not kidding, you guys. I read it first in the 80s. I've read it seven times. Six of them. My income's gone up, so I don't. I don't know how to say anything better. And you can apply it to just so many things in life. So just a. It's. It's a novel, too. It's not a mathematical. He had a mathematical theory that he wrote, and he knew nobody, none of us humans would care to read his theory, right? So he wrote a little novel about it. And if you guys are familiar with the Phoenix Project, they pattern their book a lot after his book. Um, so. So. But the Goal is the original. It's a story about a guy who runs a factory and how he improves operations, management. And, uh, I've used it in restaurants just. Just over and over and over. I've used it. So I love that.

Speaker C: Well, we needed. We needed something special to salute Ed today for his excellent comments and his performance on the TT810. So M. It needed to be something unusual and special and unprecedented. So we fondly now present the Ed Lance Dance.

Speaker B: Can't wait. When the code gets tangled and the workflow stalls, um, when the date is in pieces all over the walls, there's a guy who walks in with a laptop.

Speaker C: Lance.

Speaker B: Everybody knows him. Is the Atlant dance. He's teaching dance.

Speaker C: Right?

Speaker B: No AI here at all.

Speaker C: Uh.

Speaker D: Oh.

Speaker B: There you go.

Speaker C: All right.

Speaker B: My wife and kids are gonna want a copy of that.

Speaker C: Will do.

Speaker B: Were you the model for it, Jocelyn? Is that what it'.

Speaker D: Ed?

Speaker A: These moves are unlike anything I've ever seen.

Speaker B: Those are the best I've had in many, many years.

Speaker A: You play Frisbee? Oh, my God.

Speaker C: There you go.

Speaker B: All right. You got a lot of talent there. So.

Speaker C: Well, I listened to everything you said about AI and just put it in motion. That's all.

Speaker B: There you go. Right.

Speaker A: Outstanding. Well, you will definitely receive a copy of that and let me know what your wife thinks. But in all sincerity and, uh, honesty, thank you very much for the discussion today, Ed, because this was a fun episode and one that we've very much looking forward to doing. So we appreciate you taking the time to learn us some AI to learn more about the AI Learning revolution and move from participation to proficiency in your organization, Visit us@thetrainingassociates.com. we'll see you later.